
# 1)  When you have a weak prior and likelihood (high variance for both so not
#.     informative), the utility function heavily dictates the shape of the expected utility
#.     and final decision (the location of the max of the expected utility)

# 2) How much it helps guide your decision depends on the prior and utility function.
#.   If the likelihood is much more informative that the prior (lower variance), it
#.   will help clarify your decision of location quite a bit.

# 3) None are always the "most important". It depends on the interplay of all components,
#.   especially the information of the prior and likelihood. If you have an informative
#.  prior, that will heavily influence the posterior and thus the expected utility.
#.   If you have an informative likelihood, that will drive the posterior. And if neither
#.   is informative, the utility function becomes very important,